Currently, it is known that digital cameras provide a plurality of compression modes for image signals in accordance with the JPEG standard each of which corresponds to a given image quality mode.
For example, in its digital cameras the Canon corporation provides the quality modes termed “Super Fine”, “Fine” and “Normal” which are characterized by quantization tables used in encoding. Thus, the values of the quantization tables used for the “Normal” mode are higher than for the other modes and result in an approximation of an image which is less fine, but also with a higher level of compression.
These quantization tables are comparable to the default tables defined in the JPEG standard with respective quality parameters of 97, 93 and 73.
Thus the use of such encoding parameters makes it possible to obtain quantization tables which characterize quality modes similar to the aforementioned modes.
According to the JPEG standard, the desired quality mode is chosen definitively before the encoding of the image signal and it is not possible later to pass to another quality mode for the encoded image signal.
A rate/distortion allocation method is known which makes it possible to obtain an image signal in accordance with the JPEG2000 standard and which enables quality layers to be constructed corresponding to a target rate solely for the maximum resolution.
The objective of the rate/distortion allocation method commonly used in implementations of the JPEG2000 standard is to obtain a target rate while minimizing the distortion of an image. That method relies on an algorithm which is described in the article entitled “High performance  scalable image compression with EBCOT” by D. Taubman, which appeared in “IEEE Transactions on image processing”, Vol. 9, No. 7, July 2000, pages 1158 to 1170.
For each block of coefficients Bi of the image signal decomposed into frequency sub-bands at a plurality of resolution levels, it is possible to determine a plurality of truncation points Rin of the bitstream of the block Bi corresponding respectively to a distortion Din. The objective of this method is to optimize the points (Rin, Din) in order to minimize the total distortion
  D  =            ∑      i        ⁢          D      i              n        i            of the image with a rate constraint
      R    =                            ∑          i                ⁢                  R          i                      n            i                              ≤              R        max              ,ni being the truncation point selected for the block i. This amounts to finding the smallest value of λ such that R(λ)≦Rmax and which minimizes the equation
      (                  D        ⁡                  (          λ          )                    +              λ        ⁢                                  ⁢                  R          ⁡                      (            λ            )                                )    =            ∑      i        ⁢                  (                              D            i                          n              i                                +                      λ            ⁢                                                  ⁢                          R              i                              n                i                                                    )            .      For this, the following steps may be taken:
Initialization of the extreme values λmin and λmax,
Setting a value λ equal to
                    λ        min            +              λ        max              2    ,
Determining, for that value λ, the truncation points for all the blocks Bi which minimize the equation
            (                        D          ⁡                      (            λ            )                          +                  λ          ⁢                                          ⁢                      R            ⁡                          (              λ              )                                          )        =                  ∑        i            ⁢              (                              D            i                          n              i                                +                      λ            ⁢                                                  ⁢                          R              i                              n                i                                                    )              ,
If R(λ)>Rmax, setting λmin=λ, otherwise setting λmax=λ and looping back to the second step.
For each value of λ tested, the calculations must thus be redone considering all the blocks of the image, which may prove costly in terms of calculations and thus in execution time.
Furthermore, the rate allocation is calculated solely for the maximum resolution level in the image signal.
From the document EP 1 158 764 A2 there is also known a method of encoding an image signal in accordance with the JPEG 2000 standard and an associated method of analyzing these images in order to free up memory.
The encoding method makes it possible to obtain a JPEG2000 file structure with multiple quality layers for each resolution. Before deleting data in order to free up memory, a method of analyzing and calculating is necessary in order to determine how many quality layers will be deleted to obtain the desired rate reduction.
It should be noted that these steps of analyzing and calculating the data are repeated each time it is desired to free up memory, which proves to be disadvantageous.